1. Field of the Invention
The present invention relates to an apparatus for analyzing image information, and more particularly, to an apparatus for analyzing texture information of an image and a method therefor.
2. Description of the Related Art
Texture information of a still image is important in classifying and detecting an image. The texture information is important in classifying objects after introducing in MPEG-4 in which an object-based compression is applied. Referring to FIG. 1, an apparatus for detecting texture information from an image receives a still image and performs filtering with a Garbor filtering unit. The Garbor filtering unit is comprised of filters having a predetermined coefficient value based on characteristic scales and orientations. For example, the Garbor filtering unit can be comprised of 24 filters by combining four scales and six orientations. Namely, an input image is filtered by 24 filters having different scale and orientation coefficient values. Therefore, 24 images filtered by a filter having different filtering coefficient values are obtained. A mean and variance calculator calculates mean and variance from the filtered 24 images. Such a mean and variance value shows a regulation in the image and can be used for analyzing the texture information of the image.
However, since the apparatus extracts the mean and variance from the filtered image, it can extract information on the degree of regulation the texture has; however, it cannot analyze the orientation and the periodicity of the texture in detail.
To solve the above problem, it is an objective of the present invention to provide an apparatus for analyzing image texture information by and able to analyze the orientation and periodicity of a texture in detail.
It is another object of the present invention to provide a method for analyzing image texture information by which it is possible to analyze the orientation and periodicity of a texture in detail.
Accordingly, to achieve the first objective, there is provided an apparatus for analyzing image texture information after receiving an image, comprising: a filtering unit for filtering a still image, comprised of a plurality of pixels of M rowsxc3x97N columns, by using filters having different filtering coefficients, X axis projecting means for calculating a gray level mean value of a row of N pixels, for each row, with respect to the filtered plurality of images; and Y axis projecting means for calculating a gray level mean value of a column of M pixels, for each column, with respect to the filtered plurality of images.
It is preferable that the apparatus further comprises: graph generating means for generating graphs showing the trend of gray level mean values from the gray level mean values output from the X axis projecting means and from the Y axis projecting means, with respect to the plurality of filtered images; graph storing means for storing the graphs; and texture information analyzing means for analyzing the texture information of the image using the graphs.
The texture information analyzing means preferably analyzes the texture information of the image either using one characteristic of a group of characteristics comprised of the shape, the peak, and the periodicity of the graph, or the combination of the characteristics. The filtering unit is preferably a Garbor filter that includes filters constructed by combining different scale coefficients and different orientation coefficients.
To achieve the second objective, there is provided a method for analyzing image texture information after receiving an image, comprising: a step of reading a still image, comprised of pixels of M rowsxc3x97N columns, a step of filtering the still image using filters having different filtering coefficients, and outputting a plurality of images, an X axis projecting step for calculating a gray level mean value of a row of N pixels, for each row, with respect to the filtered plurality of images; a Y axis projecting step for calculating a gray level mean value of a column of M pixels, for each column, with respect to the filtered plurality of images a step of generating graphs showing the change of gray level mean values, with respect to the plurality of filtered images from the gray level mean values obtained in the X and Y axes projection steps; a step of storing the graphs; and a texture information analyzing step of analyzing the texture information of an image using the graphs.